NovAT tool-Reliable novel HLA alleles identification from next-generation sequencing data

HLA molecules are expressed in almost all nucleated cells of the body. These molecules are extremely variable and responsible for tissue specificity recognition. Precise HLA typing is crucial for tissue and organ transplantation. Usually, HLA-typing NGS methods are based on the assignment of reads to a certain previously reported HLA allele presented in the IPD-IMGT/HLA Database. But there is a limited number of tools able to identify novel alleles that have not yet been reported and thus absent in the database. Such alleles carry mismatches distinguishing them from all known alleles in the database. Therefore, manual evaluation of the identified HLA alleles in the genome browser is a compulsory step in the analysis, and one that is labor intensive and time consuming. We present the development and validation of a freely available web-application for the identification of novel HLA alleles in the most relevant HLA class I and II genes from NGS data. The tool can also be used for automated data quality assessment. The software was validated by analyzing 330 alleles. The results are concordant with orthogonal methods.

Automated summary

HLA molecules, expressed in almost all nucleated cells of the body, are crucial for tissue specificity recognition. Current tools have limited ability to identify novel HLA alleles, making manual evaluation of identified HLA alleles a labor-intensive and time-consuming step in the analysis.